It is widely accepted practice to apply design data quality checks during product development that are automatically enforced based upon product functionality and industry standard and/or government regulations. For example, in assembly design, a dataset must pass workflow processes at a sequence of status check points to be released at a major milestone event. One of the verifications that is performed during each workflow process is to verify that the target dataset has passed a number of validation checks. For example, dataset A is targeted to be released at major event 1, if it must pass each list of validation checks at status 0, 1, 2, 3 and so on. The list of validation checkers that are verified at each status check point may be the same with different rules which means that the same checker could be optional, that is must run but result status can be ignored, at the beginning and becomes mandated, that is must run and pass status is required, from certain status check point and on. Different types of datasets may be subject to different checks. Throughout the product development process, design data may be classified in various disciplines and subject to different quality checks at different points of time. Missing any one check could potentially cause quality issues later on.
What is needed is a system and method for validating a rule set for applicable checks of a part where parameters are verified for a checker even though the check result is passed knowing that the lists of validation checks are different from commodity to commodity.